The National Academies Press

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Pages 280-300

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From page 280... ... 280 As discussed in Chapter 7, two statistical approaches -- deterministic frequentist regression and probabilistic (Bayesian) inference -- were carried out to identify the best correlation equations between erodibility parameters and geotechnical properties. Read the entire page →
From page 281... ... Advantages Drawbacks Applications EFA 1. Minimizes the sample disturbance effect, as it takes the unextruded Shelby tube sample directly from the field. Read the entire page →
From page 282... ... 282 Relationship Between Erodibility and Properties of Soils presents remarks on the proposed equation, and gives the correction factor needed to reach 90% confidence in under- or overpredicting the measured erodibility parameter. The units used for each parameter are indicated in Table 47 (Chapter 7) Read the entire page →
From page 283... ... Most Robust Correlation Equations 283 Remarks R2 = 0.94 C.V. score = 0.66 1. Read the entire page →
From page 284... ... 284 Relationship Between Erodibility and Properties of Soils Remarks R2 = 0.50 C.V. score = 0.10 1. Read the entire page →
From page 285... ... Most Robust Correlation Equations 285 Remarks R2 = 0.64 C.V. score = 0.43 1. Read the entire page →
From page 286... ... 286 Relationship Between Erodibility and Properties of Soils Refer to Figure 146 Remarks R2 = 0.88 C.V. score = 0.72 1. Read the entire page →
From page 287... ... Most Robust Correlation Equations 287 Refer to Figure 146 Remarks R2 = 0.80 C.V. score = 0.80 1. Read the entire page →
From page 288... ... 288 Relationship Between Erodibility and Properties of Soils Remarks R2 = 0.91 C.V. score = 0.64 1. Read the entire page →
From page 289... ... Most Robust Correlation Equations 289 Remarks R2 = 0.90 C.V. score = 0.53 1. Read the entire page →
From page 290... ... 290 Relationship Between Erodibility and Properties of Soils Remarks R2 = 0.90 C.V. score = 0.67 1. Read the entire page →
From page 291... ... Most Robust Correlation Equations 291 Remarks R2 = 0.93 C.V. score = 0.23 1. Read the entire page →
From page 292... ... 292 Relationship Between Erodibility and Properties of Soils Use this equation when PF > 30%. Remarks R2 = 0.86 C.V. Read the entire page →
From page 293... ... Most Robust Correlation Equations 293 Remarks R2 = 0.81 C.V. score = 0.531 1. Read the entire page →
From page 294... ... 294 Relationship Between Erodibility and Properties of Soils Remarks R2 = 0.86 C.V. score = 0.64 1. Read the entire page →
From page 295... ... Most Robust Correlation Equations 295 Remarks R2 = 0.79 C.V. score = 0.52 1. Read the entire page →
From page 296... ... 296 Relationship Between Erodibility and Properties of Soils Remarks R2 = 0.92 C.V. score = 0.80 1. Read the entire page →
From page 297... ... Most Robust Correlation Equations 297 Remarks R2 = 0.55 C.V. score = 0.53 1. Read the entire page →
From page 298... ... 298 Relationship Between Erodibility and Properties of Soils < . Read the entire page →
From page 299... ... Most Robust Correlation Equations 299 Remarks R2 = 0.77 C.V. score = 0.78 1. Read the entire page →
From page 300... ... 300 Relationship Between Erodibility and Properties of Soils Remarks R2 = 0.70 C.V. score = 0.54 1. Read the entire page →

From page 280...

... 280 As discussed in Chapter 7, two statistical approaches -- deterministic frequentist regression and probabilistic (Bayesian) inference -- were carried out to identify the best correlation equations between erodibility parameters and geotechnical properties.